Algorithm & Data Structures Syllabus

• Introduction (6.0 h)
  • Course introduction
  • Review on C and problem solving
• Dynamic memory allocation in C (7.5 h)
  • Data representation in memory
  • Pointers (or references to objects)
  • Runtime memory management (dynamic memory allocation)
• Static and dynamic linear Abstract Data Types (ADT, 9.0 h)
  • Simple and multiple linked structures
  • Stack and queues
  • Strategies for data structure selection.
• Recursion and recursive programs (12.0 h)
  • The notion of recursion and the divide-and-conquer paradigm
  • Mathematical recursive functions
  • Simple recursive procedures
  • Recursive sorting (mergesort, quicksort, heapsort)
  • Backtrack and implementation of recursion
  • Combinatorics principle and their implementation.
• Modularity and modular implementation of algorithms and data structures (4.5 h)
  • The implementation-interface-client model
  • Implementation in C of programs with multiple source and header files
  • Basic use of development and debug tools, like make and gdb.
• Abstract objects, collections of objects, and ADTs (7.5 h)
  • Classification, definition, and examples
  • Trees
  • Binary search trees
  • Hash tables
  • Priority queues, heaps, and heap-sort.

• Greedy algorithm (1.5 h)

• Dynamic programming (1.5 h)

• Graph theory (7.5 h)
  • Graph representation
  • Visits (depth-first and breadth-first search) and their applications
  • Single-source shortest paths
  • Minimum spanning trees.
• Problem solving and practice (8.0 h)
  • Analysis and definition of strategies for data structures and algorithms
  • Search and optimization problems
  • Techniques to explore the state space based on combinatorics
• Laboratory practice (15.0 h)